Data Analytics Leadership Recruitment
A common frustration of functional Data Leadership executives is when they are overlooked for a role by a Company or a Search Firm on the basis that they lack knowledge or experience of working in that sector.
The feeling is that this is an unfair basis on which to judge their suitability for the role, particularly if it prevents them from even getting to the interview process where they can demonstrate their capability in person.
The most common argument is that “Data is Data at the end of the day!”
It’s true that Data is, of course, Data. But it is also true that not all Data is of equal value and importance to a business, and in many cases it is only deep domain knowledge or sector familiarity that can judge this.
Data Leaders are many things but they are often good at being 2 things: Translators & Organisers. Both these things usually require that person to have strong domain expertise. Let’s examine why:
As a Translator it’s your job to identify the value AI & Analytics effectively in the business context. To do that you are going to need to understand the key metrics of that particular business, and how changes in those metrics will likely impact performance on revenue, p&L, customer retention etc.
If you do not deeply understand these metrics and what change can mean you cannot be an effective translator
Particularly within large corporates who have access to different kinds of Data and lots of it , one of the major challenges of the Data Analytics leader is to decide where to start in the pursuit of value. How should you organise your team and on what projects? Where can you have the quickest wins? What long term high value projects might you focus on?
Organising your troops in the most optimal way is going to far easier the more you know about your domain, and the more you understand what are the crucial factors that drive revenue & profits. This will allow you to have the most impact on the business, and in the shortest amount of time possible.
There are exceptions. Sometimes an individual from a different domain can bring crucial experience and different ways of doing things that have huge benefits. But in most cases Domain experience means an easy transition and the ability to add value more quickly. As Data and business have collided in recent years this has never been truer.